{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "139002ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penri\\AppData\\Local\\Temp\\ipykernel_27624\\2979793285.py:9: DeprecationWarning: `set_matplotlib_formats` is deprecated since IPython 7.23, directly use `matplotlib_inline.backend_inline.set_matplotlib_formats()`\n",
      "  set_matplotlib_formats('retina')\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Day</th>\n",
       "      <th>Group</th>\n",
       "      <th>Originality</th>\n",
       "      <th>Interestingness</th>\n",
       "      <th>Writing</th>\n",
       "      <th>Coherence</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Evaluator</th>\n",
       "      <th>unique_id</th>\n",
       "      <th>external</th>\n",
       "      <th>Humanlikeness</th>\n",
       "      <th>English</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Ability</th>\n",
       "      <th>DAT</th>\n",
       "      <th>Total</th>\n",
       "      <th>Idea</th>\n",
       "      <th>Outline</th>\n",
       "      <th>Write</th>\n",
       "      <th>Edit</th>\n",
       "      <th>Satisfaction</th>\n",
       "      <th>Flexibility</th>\n",
       "      <th>Goal</th>\n",
       "      <th>Again</th>\n",
       "      <th>AI_Helpfulness</th>\n",
       "      <th>AI_Satisfaction</th>\n",
       "      <th>AI_Contribution</th>\n",
       "      <th>DAT_Group</th>\n",
       "      <th>Group_</th>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
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       "      <td>Human Creativity</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Benjamin Joers</td>\n",
       "      <td>1_1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>86.81</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Human Creativity</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Rio Dharma</td>\n",
       "      <td>1_1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>86.81</td>\n",
       "      <td>80.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Human Creativity</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>allison liegner</td>\n",
       "      <td>1_2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>86.81</td>\n",
       "      <td>85.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Human Creativity</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Ryan Ho</td>\n",
       "      <td>1_2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>86.81</td>\n",
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       "      <td>15.0</td>\n",
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       "      <td>70.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Human Confirmation</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Nathan Kidambi</td>\n",
       "      <td>2_1</td>\n",
       "      <td>0</td>\n",
       "      <td>6.5</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
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       "      <td>4</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>Pema Euden</td>\n",
       "      <td>294_2</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>87.08</td>\n",
       "      <td>45.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>2192</th>\n",
       "      <td>295</td>\n",
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       "      <td>Human Creativity</td>\n",
       "      <td>5</td>\n",
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       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>6.5</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2193</th>\n",
       "      <td>295</td>\n",
       "      <td>1</td>\n",
       "      <td>Human Creativity</td>\n",
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       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Alan Wu</td>\n",
       "      <td>295_1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>74.63</td>\n",
       "      <td>66.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>40.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2194</th>\n",
       "      <td>295</td>\n",
       "      <td>2</td>\n",
       "      <td>Human Creativity</td>\n",
       "      <td>5</td>\n",
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       "      <td>6</td>\n",
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       "      <td>55.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2195</th>\n",
       "      <td>295</td>\n",
       "      <td>2</td>\n",
       "      <td>Human Creativity</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Ziqi Yang</td>\n",
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       "      <td>71.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2196 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID  Day               Group  Originality  Interestingness  Writing  \\\n",
       "0       1    1    Human Creativity            5                3        4   \n",
       "1       1    1    Human Creativity            5                6        4   \n",
       "2       1    2    Human Creativity            2                1        3   \n",
       "3       1    2    Human Creativity            6                7        7   \n",
       "4       2    1  Human Confirmation            6                5        6   \n",
       "...   ...  ...                 ...          ...              ...      ...   \n",
       "2191  294    2             Copilot            6                4        5   \n",
       "2192  295    1    Human Creativity            5                4        4   \n",
       "2193  295    1    Human Creativity            5                5        6   \n",
       "2194  295    2    Human Creativity            5                5        5   \n",
       "2195  295    2    Human Creativity            5                5        7   \n",
       "\n",
       "      Coherence  Overall        Evaluator unique_id  external  Humanlikeness  \\\n",
       "0             7      4.0   Benjamin Joers       1_1         0            4.5   \n",
       "1             5      5.0       Rio Dharma       1_1         0            4.5   \n",
       "2             5      2.0  allison liegner       1_2         0            3.0   \n",
       "3             6      7.0          Ryan Ho       1_2         0            3.0   \n",
       "4             6      6.0   Nathan Kidambi       2_1         0            6.5   \n",
       "...         ...      ...              ...       ...       ...            ...   \n",
       "2191          5      5.0       Pema Euden     294_2         1            3.0   \n",
       "2192          4      4.0       Pema Euden     295_1         1            6.5   \n",
       "2193          5      5.0          Alan Wu     295_1         1            6.5   \n",
       "2194          6      5.0       Pema Euden     295_2         1            3.5   \n",
       "2195          7      6.0        Ziqi Yang     295_2         1            3.5   \n",
       "\n",
       "      English  Experience  Ability    DAT  Total  Idea  Outline  Write  Edit  \\\n",
       "0         3.0         1.0      2.0  86.81   80.0  12.0      8.0   55.0   5.0   \n",
       "1         3.0         1.0      2.0  86.81   80.0  12.0      8.0   55.0   5.0   \n",
       "2         3.0         1.0      2.0  86.81   85.0  10.0     20.0   15.0  40.0   \n",
       "3         3.0         1.0      2.0  86.81   85.0  10.0     20.0   15.0  40.0   \n",
       "4         2.0         1.0      1.0  89.58    NaN  45.0      NaN    NaN   NaN   \n",
       "...       ...         ...      ...    ...    ...   ...      ...    ...   ...   \n",
       "2191      3.0         3.0      2.0  87.08   45.0   3.0      5.0   25.0  12.0   \n",
       "2192      2.0         1.0      1.0  74.63   66.0   1.0      5.0   40.0  20.0   \n",
       "2193      2.0         1.0      1.0  74.63   66.0   1.0      5.0   40.0  20.0   \n",
       "2194      2.0         1.0      1.0  74.63   55.0   5.0     20.0   25.0   5.0   \n",
       "2195      2.0         1.0      1.0  74.63   55.0   5.0     20.0   25.0   5.0   \n",
       "\n",
       "      Satisfaction  Flexibility  Goal  Again  AI_Helpfulness  AI_Satisfaction  \\\n",
       "0              1.0          4.0   2.0    0.0             NaN              NaN   \n",
       "1              1.0          4.0   2.0    0.0             NaN              NaN   \n",
       "2              3.0          3.0   3.0    0.0             4.0              5.0   \n",
       "3              3.0          3.0   3.0    0.0             4.0              5.0   \n",
       "4              2.0          6.0   2.0    0.0             NaN              NaN   \n",
       "...            ...          ...   ...    ...             ...              ...   \n",
       "2191           7.0          6.0   5.0    1.0             7.0              7.0   \n",
       "2192           5.0          4.0   2.0    0.0             NaN              NaN   \n",
       "2193           5.0          4.0   2.0    0.0             NaN              NaN   \n",
       "2194           3.0          4.0   5.0    1.0             6.0              5.0   \n",
       "2195           3.0          4.0   5.0    1.0             6.0              5.0   \n",
       "\n",
       "      AI_Contribution  DAT_Group  Group_  \n",
       "0                 NaN          3       1  \n",
       "1                 NaN          3       1  \n",
       "2                70.0          3       1  \n",
       "3                70.0          3       1  \n",
       "4                 NaN          3       2  \n",
       "...               ...        ...     ...  \n",
       "2191             91.0          3       3  \n",
       "2192              NaN          2       1  \n",
       "2193              NaN          2       1  \n",
       "2194             71.0          2       1  \n",
       "2195             71.0          2       1  \n",
       "\n",
       "[2196 rows x 30 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import matplotlib.transforms as transforms\n",
    "import seaborn as sns\n",
    "from IPython.display import set_matplotlib_formats\n",
    "%matplotlib inline\n",
    "set_matplotlib_formats('retina')\n",
    "from scipy import stats\n",
    "import statsmodels.formula.api as smf\n",
    "import statsmodels.api as sm\n",
    "import warnings\n",
    "import matplotlib.path as mpath\n",
    "sns.set(rc={\"figure.dpi\":100, 'savefig.dpi':300})\n",
    "sns.set_context('notebook')\n",
    "sns.set_style(\"ticks\")\n",
    "warnings.filterwarnings('ignore')\n",
    "pd.set_option('display.max_columns', None)\n",
    "df = pd.read_csv('Replication Data for Designing Human and Generative AI Collaboration.csv').iloc[:,1:]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfed4b42",
   "metadata": {},
   "source": [
    "# A. Completion Time Across Groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "63e9f0c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1772.38x400 with 5 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 427,
       "width": 1556
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp = df.groupby(by=['ID', 'Day'])[['Group', 'Total', 'Idea', 'Outline', 'Write', 'Edit']].first().reset_index()\n",
    "tmp = tmp.rename(columns={'Idea':'Ideation', 'Outline': 'Outlining', 'Write': 'Drafting', 'Edit':'Editing'})\n",
    "tmp2 = pd.melt(tmp, id_vars=[\"ID\", 'Group', 'Day'], var_name='Total', value_name=\"Time\")\n",
    "tmp2.Day = tmp2.Day.astype('str')\n",
    "tmp2.Day.replace({'1':'Writing without AI', '2':'Writing with AI'}, inplace=True)\n",
    "\n",
    "# Set figure size\n",
    "#mpl.rcParams['figure.figsize'] = (2, 3)\n",
    "\n",
    "# Create the catplot\n",
    "ax = sns.catplot(\n",
    "    kind='bar',\n",
    "    data=tmp2,\n",
    "    x='Group',\n",
    "    y='Time',\n",
    "    hue='Day',\n",
    "    col='Total',\n",
    "    order=['Human Confirmation', 'Human Creativity', 'Copilot'],\n",
    "    palette=sns.color_palette(['gray', 'white']),\n",
    "    edgecolor=\"k\",\n",
    "    width=0.8,\n",
    "    height=4,\n",
    "    aspect=0.8,\n",
    "    errorbar=('ci', 95),\n",
    "    capsize=0.1,\n",
    "    errwidth=0.5\n",
    ")\n",
    "\n",
    "# Remove axis labels\n",
    "ax.set(xlabel='', ylabel='')\n",
    "\n",
    "# Set custom x-tick labels\n",
    "plt.xticks([0, 1, 2], ['Human\\nConfirmation', 'Human\\nCreativity', 'Copilot'])\n",
    "\n",
    "# Move the legend, remove its title, and arrange items side by side\n",
    "sns.move_legend(\n",
    "    ax,\n",
    "    \"upper center\",\n",
    "    bbox_to_anchor=(0.47, 1.1),\n",
    "    fontsize=15,\n",
    "    ncol=2  # Arrange legend items side by side\n",
    ")\n",
    "\n",
    "# Remove the legend title\n",
    "ax._legend.set_title('')\n",
    "\n",
    "# Set the titles of the facets\n",
    "ax.set_titles(\"{col_name}\", size=20)\n",
    "\n",
    "# Annotate bars and adjust margins\n",
    "for axis in ax.axes.ravel():\n",
    "    # Add annotations\n",
    "    for c in axis.containers:\n",
    "        axis.bar_label(c, label_type='edge', fmt='{:,.1f}', padding=10)\n",
    "    axis.margins(y=0.2)\n",
    "\n",
    "# Optionally set y-axis limits\n",
    "# plt.ylim(4, 5.5)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n",
    "\n",
    "ax.figure.savefig(\"Fig 1A - Completion Time Across Groups.pdf\", bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "582c593e",
   "metadata": {},
   "source": [
    "# B. Completion Time Inequality Decreases With AI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7ebb1735",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 484,
       "width": 584
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import statsmodels.api as sm\n",
    "import seaborn as sns\n",
    "from matplotlib.lines import Line2D\n",
    "\n",
    "df['High'] = df['Idea'] + df['Outline']\n",
    "df['Low'] = df['Write'] + df['Edit']\n",
    "\n",
    "t1 = df[df.Day == 1]\n",
    "t2 = df[df.Day == 2]\n",
    "\n",
    "t1_ = t1.groupby(by='ID')['Total'].mean().reset_index()\n",
    "t1_ = pd.merge(t1_, t1[['ID', 'Group', 'English', 'Experience', 'Ability', 'DAT']], on=['ID']).drop_duplicates(keep='first').reset_index(drop=True)\n",
    "t2_ = t2.groupby(by='ID')['Total'].mean().reset_index()\n",
    "t2_ = pd.merge(t2_, t2[['ID', 'Group']], on=['ID']).drop_duplicates(keep='first').reset_index(drop=True)\n",
    "tt_ = pd.merge(t1_, t2_, on=['ID', 'Group'], how='left')\n",
    "\n",
    "tt__ = tt_.copy()\n",
    "\n",
    "def round_to_nearest_half(x):\n",
    "    return np.round(x/10) * 10  # return np.round(x * 2) / 2\n",
    "\n",
    "tt__['Total_x'] = tt__['Total_x'].apply(round_to_nearest_half)\n",
    "tt__['Total_y'] = tt__['Total_y'].apply(round_to_nearest_half)\n",
    "\n",
    "tt__['Total_x'] = np.where(tt__['Total_x'] > 90, 90, tt__['Total_x'])\n",
    "tt__['Total_y'] = np.where(tt__['Total_y'] > 90, 90, tt__['Total_y'])\n",
    "\n",
    "# 1. Remove rows with NaN values in the relevant columns, including control variables\n",
    "tt_clean = tt_.dropna(subset=['Total_x', 'Total_y', 'English', 'Experience', 'Ability', 'DAT'])\n",
    "\n",
    "# 2. Data Aggregation\n",
    "aggregated_data = tt__.groupby(['Total_x', 'Group']).agg(\n",
    "    mean_y=('Total_y', 'mean'),\n",
    "    count=('Total_y', 'size')\n",
    ").reset_index()\n",
    "\n",
    "# 3. Prepare the Plot\n",
    "fig, ax = plt.subplots(figsize=(6, 5))\n",
    "\n",
    "# Remove grid\n",
    "ax.grid(False)\n",
    "\n",
    "# Define markers and line styles for each group\n",
    "group_markers = {\n",
    "    \"Human Confirmation\": 'o',  # Circle\n",
    "    \"Human Creativity\": 'x',    # X marker\n",
    "    \"Copilot\": '^'              # Triangle\n",
    "}\n",
    "\n",
    "group_linestyles = {\n",
    "    \"Human Confirmation\": 'solid',   # Solid line\n",
    "    \"Human Creativity\": 'dashed',    # Dashed line\n",
    "    \"Copilot\": 'dotted'              # Dotted line\n",
    "}\n",
    "\n",
    "# Define the desired order of groups\n",
    "groups = ['Human Confirmation', 'Human Creativity', 'Copilot']\n",
    "\n",
    "# Map counts to sizes between 40 and 200 for marker sizes\n",
    "count_min = aggregated_data['count'].min()\n",
    "count_max = aggregated_data['count'].max()\n",
    "\n",
    "def map_size(count, count_min, count_max, size_min=40, size_max=200):\n",
    "    if count_max == count_min:\n",
    "        return size_min\n",
    "    else:\n",
    "        return size_min + (count - count_min) * (size_max - size_min) / (count_max - count_min)\n",
    "\n",
    "# Prepare to store regression results for legend\n",
    "legend_handles = []\n",
    "\n",
    "# Loop through each group\n",
    "for idx, group in enumerate(groups):\n",
    "    # Prepare data for plotting\n",
    "    group_data_agg = aggregated_data[aggregated_data['Group'] == group]\n",
    "    x_agg = group_data_agg['Total_x']\n",
    "    y_agg = group_data_agg['mean_y']\n",
    "    counts = group_data_agg['count']\n",
    "    sizes = counts.apply(lambda c: map_size(c, count_min, count_max))\n",
    "    marker = group_markers[group]\n",
    "    \n",
    "    # Conditionally set facecolor and color based on the marker type\n",
    "    if marker == 'x':  # X marker: Use 'color' argument for black color\n",
    "        ax.scatter(\n",
    "            x_agg, y_agg, s=sizes, marker=marker, color='black',  # Ensure x is black\n",
    "            alpha=0.5, zorder=2\n",
    "        )\n",
    "    else:\n",
    "        # Other markers can use unfilled style\n",
    "        ax.scatter(\n",
    "            x_agg, y_agg, s=sizes, marker=marker, facecolors='none',\n",
    "            edgecolors='black', alpha=0.5, zorder=2\n",
    "        )\n",
    "    \n",
    "    # Regression analysis with control variables\n",
    "    group_data = tt_clean[tt_clean['Group'] == group]\n",
    "    X = group_data[['Total_x', 'English', 'Experience', 'Ability', 'DAT']]\n",
    "    y = group_data['Total_y']\n",
    "    \n",
    "    # Add constant term for intercept\n",
    "    X = sm.add_constant(X)\n",
    "    \n",
    "    # Fit OLS regression model\n",
    "    model = sm.OLS(y, X).fit()\n",
    "    slope = model.params['Total_x']\n",
    "    \n",
    "    # Get the confidence intervals for the slope\n",
    "    conf_int = model.conf_int().loc['Total_x']\n",
    "    ci_lower = conf_int[0]\n",
    "    ci_upper = conf_int[1]\n",
    "    \n",
    "    # Generate regression line values over x = [min_x, max_x]\n",
    "    x_min = 35 #tt_['Total_x'].min()\n",
    "    x_max = tt_['Total_x'].max()\n",
    "    x_vals = np.linspace(x_min, x_max, 100)\n",
    "    \n",
    "    # Create a DataFrame for plotting the regression line, with mean values for control variables\n",
    "    control_means = group_data[['English', 'Experience', 'Ability', 'DAT']].mean()\n",
    "    X_plot = pd.DataFrame({\n",
    "        'const': 1,\n",
    "        'Total_x': x_vals,\n",
    "        'English': control_means['English'],\n",
    "        'Experience': control_means['Experience'],\n",
    "        'Ability': control_means['Ability'],\n",
    "        'DAT': control_means['DAT']\n",
    "    })\n",
    "    y_vals = model.predict(X_plot)\n",
    "    \n",
    "    # Line style for the group\n",
    "    linestyle = group_linestyles[group]\n",
    "    \n",
    "    # Plot regression line\n",
    "    ax.plot(\n",
    "        x_vals, y_vals, linestyle=linestyle, color='black', zorder=3\n",
    "    )\n",
    "    \n",
    "    # Prepare label with slope and confidence intervals\n",
    "    slope_formatted = f\"{slope:.2f}\"\n",
    "    ci_lower_formatted = f\"{ci_lower:.2f}\"\n",
    "    ci_upper_formatted = f\"{ci_upper:.2f}\"\n",
    "    label = f\"{group} (Slope: {slope_formatted}, 95% CI = [{ci_lower_formatted}, {ci_upper_formatted}])\"\n",
    "    \n",
    "    # Create Line2D object for legend, including marker with black face color\n",
    "    line_handle = Line2D(\n",
    "        [0], [0],\n",
    "        color='black',\n",
    "        linestyle=linestyle,\n",
    "        marker=marker,\n",
    "        markerfacecolor='black',   # Filled marker with black color\n",
    "        markeredgecolor='black',\n",
    "        markersize=8,\n",
    "        alpha=0.8,\n",
    "        label=label\n",
    "    )\n",
    "    legend_handles.append(line_handle)\n",
    "    \n",
    "# Adjust plot limits based on data\n",
    "ax.set_xlim(35, 95)\n",
    "ax.set_ylim(-5, 80)\n",
    "\n",
    "# Move legend to lower right without border\n",
    "ax.legend(handles=legend_handles, frameon=False, loc='lower left')\n",
    "\n",
    "# Set labels and title\n",
    "ax.set_xlabel('Total Completion Time (Day 1, Without AI)', labelpad=5, fontsize=14)\n",
    "ax.set_ylabel('Total Completion Time (Day 2, With AI)', labelpad=5, fontsize=14)\n",
    "\n",
    "# Adjust layout and show plot\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "ax.figure.savefig(\"Fig 1B - Completion Time Inequality Decreases With AI.pdf\", bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88de53c9",
   "metadata": {},
   "source": [
    "# Percentage Reduction in Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b4a3f7d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.3615941118607462\n",
      "0.6860529676308921\n"
     ]
    }
   ],
   "source": [
    "# Total\n",
    "print((df[df.Day==1]['Total'].mean() - df[df.Day==2]['Total'].mean()) / df[df.Day==1]['Total'].mean())\n",
    "# Writing\n",
    "print((df[df.Day==1]['Write'].mean() - df[df.Day==2]['Write'].mean()) / df[df.Day==1]['Write'].mean())"
   ]
  },
  {
   "cell_type": "code",
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   "id": "cbc42dab",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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